10-810 Computational Molecular Biology: A Machine Learning Approach

Units: 12.0 Department: Center for Auto. Learning & Disc. Cross-listed: 03-715 Related URLs: http://www.cmu.edu This course focuses on modern machine learning methodologies for computational problems in molecular biology and genetics, including probabilistic modeling, inference and learning algorithms, Bayesian methods, pattern recognition, data fusion, time series analysis, etc. We will discuss the following biological problems: 1) Analysis of high throughput biological data, such as gene expression data, focusing on issues ranging from data acquisition to pattern recognition and classification. 2) Computational genomics, focusing on gene finding, motifs detection, sequence evolution and comparative genomics. 3) Systems biology, concerning how to combine sequence, expression and other biological data sources (protein-protein interaction, protein-DNA binding and more) to infer the structure and function of different systems in the cell.

Popularity index Rank for this semester: #1298 Rank in this department: #2   Students also scheduled 79-104 Introduction to World History 21-112 Calculus II 69-175 Dance for Non-Majors (Fusion of Dan... 69-158 Beginning/Intermediate Yoga 62-218 Sparta, Greece: Inquiry and Vision 51-262 Communication Design Fundamentals 67-101 Colloquium: Perspectives in Informa... 51-231 Calligraphy I

Spring 2005 times

Sec	Time	Day	Instructor	Location
A	3:00 - 4:20 pm	M	Xing, Bar-Joseph	WEH 4615A
		W	Xing, Bar-Joseph	WEH 4615A